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A serverless vector database

built from first principles on object storage: 10-100x cheaper, usage-based pricing, and massive scalability

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Trusted in prod by...

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Cost calculator

Query latency

1m documents

Warm queries have all their data in cache.

Percentile
Latency
P50
28ms
P90
37ms
P99
63ms
MAX
98ms

Approach: Search for 100 random vectors from the 768d dataset with top k = 10, when dataset is fully in cache. Warming the cache for an index takes about ~10s (for 1m vectors) after the first cold query, and typically stays in cache for a few hours.

Trusted in production by

"

Justin Watts

Distinguished Engineer

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Moving to turbopuffer felt less like an upgrade and more like discovering a new paradigm. We didn't just save costs; we turned once-prohibitive features into standard tools in our arsenal. Vectorize all the things and say goodbye to sharding

MTL 🇨🇦

single-tenant cluster

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Limits
MetricMax seen in productionProduction limits (current)Production limits (soon)
Max documents (global)35B+Unlimited
Max documents (per namespace)180M100M1B+
Number of namespaces10M+Unlimited
Max dimensions10,752
Max inactive time in cache~3 daysContact us for custom
Write rate (global)100,000 doc/sUnlimited
Write rate (per namespace)10,000 doc/sUnlimited
Queries (global)1000+ queries/sUnlimited
Max queries/second (per namespace)100+ queries/s100+ queries/s10,000 QPS
Vector search recall@10~90-95%~90-95%Configurable
Max attribute value8 MiB8 MiB
See full list and workloads that are a great fit for turbopuffer 🐡

FAQ

Yes, turbopuffer is production quality. We have powered production applications since November '23 at 99.99% uptime. We host billions of production vectors at thousands of writes per second.

We maintain SOC2 Type 2 certification and HIPAA compliance.

turbopuffer accounts are not yet generally available. We are currently focused on providing high bandwidth support to make our select early customers successful, while removing limitations. See if your workload is a good fit for turbopuffer here.

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